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2025-2025
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Evaluating the techno-economic potential of large-scale green hydrogen production via solar, wind, and hybrid energy systems utilizing PEM and alkaline electrolyzers
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BV
Authors: Hassan Munther; Qusay Hassan; Anees A. Khadom; Hameed B. Mahood;
doi: 10.1016/j.uncres.2024.100122
doi: 10.1016/j.uncres.2024.100122
Unconventional Resou...arrow_drop_down
Unconventional Resources
Article . 2025 . Peer-reviewed
License: CC BY
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Unconventional Resou...arrow_drop_down
Unconventional Resources
Article . 2025 . Peer-reviewed
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A short term multistep forecasting model for photovoltaic generation using deep learning model
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BV
Authors: Lakshmi P. Dinesh; Nameer Al Khafaf; Brendan McGrath;
doi: 10.1016/j.susoc.2024.11.003
doi: 10.1016/j.susoc.2024.11.003
Sustainable Operatio...arrow_drop_down
Sustainable Operations and Computers
Article . 2025 . Peer-reviewed
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Sustainable Operations and Computers
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Latent-dry: Solar drying with latent heat storage in Python, Fortran and TRNSYS
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BVFunded by:
[no funder available]
Authors: Franz Román; Oliver Hensel;
doi: 10.1016/j.softx.2024.101999
doi: 10.1016/j.softx.2024.101999
SoftwareXarrow_drop_down
SoftwareX
Article . 2025 . Peer-reviewed
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SoftwareX
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Calculating the impact of replacing legacy batteries with standardized lithium-ion versions in defense aircraft
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BV
Authors: Brandon J. Hopkins; Fernando T. Tavares;
doi: 10.1016/j.nxener.2024.100208
doi: 10.1016/j.nxener.2024.100208
Next Energyarrow_drop_down
Next Energy
Article . 2025 . Peer-reviewed
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Next Energy
Article . 2025 . Peer-reviewed
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Three-dimensional computational fluid dynamics (3D-CFD) simulation of hydrogen transport to investigate the effect of output voltage and inlet anode velocity on proton exchange membrane fuel cell performances
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BV
Authors: Abdelaziz Samris; Hamid Mounir;
doi: 10.1016/j.rechem.2024.101929
doi: 10.1016/j.rechem.2024.101929
Results in Chemistryarrow_drop_down
Results in Chemistry
Article . 2025 . Peer-reviewed
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Results in Chemistryarrow_drop_down
Results in Chemistry
Article . 2025 . Peer-reviewed
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Design and experimental characterization of a propane-based reversible dual source/sink heat pump
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BVFunded by:EC | TRI-HP
EC| TRI-HP
Authors: Xabier Peña-Anton; Laura Alonso; Koldo Martin-Escudero; Zigor Uriondo; +1 Authors
Xabier Peña-Anton; Laura Alonso; Koldo Martin-Escudero; Zigor Uriondo; Eneko Setien;
doi: 10.1016/j.applthermaleng.2024.124527
doi: 10.1016/j.applthermaleng.2024.124527
Applied Thermal Engi...arrow_drop_down
Applied Thermal Engineering
Article . 2025 . Peer-reviewed
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Applied Thermal Engineering
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Further development of offshore floating solar and its design requirements
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BV
Authors: Arefeh Emami; Madjid Karimirad;
doi: 10.1016/j.marstruc.2024.103730
doi: 10.1016/j.marstruc.2024.103730
Marine Structuresarrow_drop_down
Marine Structures
Article . 2025 . Peer-reviewed
License: Elsevier TDM
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Marine Structures
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A review on hybrid energy generation: Cow dung biogas, solar thermal and kinetic energy integration for power production
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BV
Authors: Amam Hossain Bagdadee; Argho Moy Maitraya; Ariful Islam; Md. Noor E Alam Siddique;
doi: 10.1016/j.enbenv.2023.09.004
doi: 10.1016/j.enbenv.2023.09.004
Energy and Built Env...arrow_drop_down
Energy and Built Environment
Article . 2025 . Peer-reviewed
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Energy and Built Env...arrow_drop_down
Energy and Built Environment
Article . 2025 . Peer-reviewed
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Assessment and ranking of different vehicles carbon footprint: A comparative study utilizing entropy and TOPSIS methodologies
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BV
Authors: Farzan Ashraf; Azhar Equbal; Osama Khan; Zeinebou Yahya; +3 Authors
Farzan Ashraf; Azhar Equbal; Osama Khan; Zeinebou Yahya; Aiyeshah Alhodaib; Mohd Parvez; Shadab Ahmad;
doi: 10.1016/j.grets.2024.100128
doi: 10.1016/j.grets.2024.100128
Green Technologies a...arrow_drop_down
Green Technologies and Sustainability
Article . 2025 . Peer-reviewed
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Predictive Energy Demand and Optimization in Metro Systems Using AI and IoT Technologies
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:AG Editor (Argentina)
Authors: Mohammed Hatim Rziki; Abdelaaziz Hessane; Mohamed Khalifa Boutahir; Hamid Bourray; +2 Authors
Mohammed Hatim Rziki; Abdelaaziz Hessane; Mohamed Khalifa Boutahir; Hamid Bourray; Moulay Driss El Ouadghiri; Ritai Belkadi;
doi: 10.56294/dm2025467
doi: 10.56294/dm2025467
Introduction: With the rapid urbanization of modern cities, metro systems have become indispensable for efficient mobility. However, the increasing demand for public transportation has led to rising energy consumption, posing significant challenges for operational sustainability. Current energy management strategies in metro networks rely on static models and centralized systems, which often fail to adapt to real-time fluctuations in energy demand, leading to inefficiencies and wasted resources. Methods: This paper proposes an innovative approach to optimizing energy demand in metro systems by integrating Artificial Intelligence (AI) and the Internet of Things (IoT). By leveraging real-time data collected from IoT sensors deployed throughout the metro network, we apply machine learning algorithms such as Random Forests and Neural Networks to dynamically predict energy demand. These predictions enable metro operators to adjust energy consumption in real-time, thus improving overall system efficiency and reducing operational waste. Our approach was validated using data from the Parisian metro system through extensive simulations. Results: The results of simulations demonstrate significant improvements in energy efficiency. Optimized energy demand management led to a reduction in wasted energy during metro operations, particularly through the utilization of regenerative braking systems. Conclusions: Our findings suggest that integrating AI and IoT technologies into metro systems significantly improves energy efficiency by enabling dynamic energy demand prediction and real-time adjustment of energy consumption. The proposed system is scalable and adaptable, making it suitable for application in metro networks globally, thereby enhancing energy efficiency and supporting sustainable transport initiatives.
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Data & Metadata
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The following results are related to Energy Research. Are you interested to view more results? Visit OpenAIRE - Explore.

128 Research products

download

Evaluating the techno-economic potential of large-scale green hydrogen production via solar, wind, and hybrid energy systems utilizing PEM and alkaline electrolyzers
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BV
Authors: Hassan Munther; Qusay Hassan; Anees A. Khadom; Hameed B. Mahood;
doi: 10.1016/j.uncres.2024.100122
doi: 10.1016/j.uncres.2024.100122
Unconventional Resou...arrow_drop_down
Unconventional Resources
Article . 2025 . Peer-reviewed
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A short term multistep forecasting model for photovoltaic generation using deep learning model
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BV
Authors: Lakshmi P. Dinesh; Nameer Al Khafaf; Brendan McGrath;
doi: 10.1016/j.susoc.2024.11.003
doi: 10.1016/j.susoc.2024.11.003
Sustainable Operatio...arrow_drop_down
Sustainable Operations and Computers
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Latent-dry: Solar drying with latent heat storage in Python, Fortran and TRNSYS
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BVFunded by:
[no funder available]
Authors: Franz Román; Oliver Hensel;
doi: 10.1016/j.softx.2024.101999
doi: 10.1016/j.softx.2024.101999
SoftwareXarrow_drop_down
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Calculating the impact of replacing legacy batteries with standardized lithium-ion versions in defense aircraft
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BV
Authors: Brandon J. Hopkins; Fernando T. Tavares;
doi: 10.1016/j.nxener.2024.100208
doi: 10.1016/j.nxener.2024.100208
Next Energyarrow_drop_down
Next Energy
Article . 2025 . Peer-reviewed
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Next Energy
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Three-dimensional computational fluid dynamics (3D-CFD) simulation of hydrogen transport to investigate the effect of output voltage and inlet anode velocity on proton exchange membrane fuel cell performances
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BV
Authors: Abdelaziz Samris; Hamid Mounir;
doi: 10.1016/j.rechem.2024.101929
doi: 10.1016/j.rechem.2024.101929
Results in Chemistryarrow_drop_down
Results in Chemistry
Article . 2025 . Peer-reviewed
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Results in Chemistry
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Design and experimental characterization of a propane-based reversible dual source/sink heat pump
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BVFunded by:EC | TRI-HP
EC| TRI-HP
Authors: Xabier Peña-Anton; Laura Alonso; Koldo Martin-Escudero; Zigor Uriondo; +1 Authors
Xabier Peña-Anton; Laura Alonso; Koldo Martin-Escudero; Zigor Uriondo; Eneko Setien;
doi: 10.1016/j.applthermaleng.2024.124527
doi: 10.1016/j.applthermaleng.2024.124527
Applied Thermal Engi...arrow_drop_down
Applied Thermal Engineering
Article . 2025 . Peer-reviewed
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Applied Thermal Engineering
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Further development of offshore floating solar and its design requirements
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BV
Authors: Arefeh Emami; Madjid Karimirad;
doi: 10.1016/j.marstruc.2024.103730
doi: 10.1016/j.marstruc.2024.103730
Marine Structuresarrow_drop_down
Marine Structures
Article . 2025 . Peer-reviewed
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A review on hybrid energy generation: Cow dung biogas, solar thermal and kinetic energy integration for power production
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BV
Authors: Amam Hossain Bagdadee; Argho Moy Maitraya; Ariful Islam; Md. Noor E Alam Siddique;
doi: 10.1016/j.enbenv.2023.09.004
doi: 10.1016/j.enbenv.2023.09.004
Energy and Built Env...arrow_drop_down
Energy and Built Environment
Article . 2025 . Peer-reviewed
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Energy and Built Environment
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Assessment and ranking of different vehicles carbon footprint: A comparative study utilizing entropy and TOPSIS methodologies
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Elsevier BV
Authors: Farzan Ashraf; Azhar Equbal; Osama Khan; Zeinebou Yahya; +3 Authors
Farzan Ashraf; Azhar Equbal; Osama Khan; Zeinebou Yahya; Aiyeshah Alhodaib; Mohd Parvez; Shadab Ahmad;
doi: 10.1016/j.grets.2024.100128
doi: 10.1016/j.grets.2024.100128
Green Technologies a...arrow_drop_down
Green Technologies and Sustainability
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Predictive Energy Demand and Optimization in Metro Systems Using AI and IoT Technologies
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:AG Editor (Argentina)
Authors: Mohammed Hatim Rziki; Abdelaaziz Hessane; Mohamed Khalifa Boutahir; Hamid Bourray; +2 Authors
Mohammed Hatim Rziki; Abdelaaziz Hessane; Mohamed Khalifa Boutahir; Hamid Bourray; Moulay Driss El Ouadghiri; Ritai Belkadi;
doi: 10.56294/dm2025467
doi: 10.56294/dm2025467
Introduction: With the rapid urbanization of modern cities, metro systems have become indispensable for efficient mobility. However, the increasing demand for public transportation has led to rising energy consumption, posing significant challenges for operational sustainability. Current energy management strategies in metro networks rely on static models and centralized systems, which often fail to adapt to real-time fluctuations in energy demand, leading to inefficiencies and wasted resources. Methods: This paper proposes an innovative approach to optimizing energy demand in metro systems by integrating Artificial Intelligence (AI) and the Internet of Things (IoT). By leveraging real-time data collected from IoT sensors deployed throughout the metro network, we apply machine learning algorithms such as Random Forests and Neural Networks to dynamically predict energy demand. These predictions enable metro operators to adjust energy consumption in real-time, thus improving overall system efficiency and reducing operational waste. Our approach was validated using data from the Parisian metro system through extensive simulations. Results: The results of simulations demonstrate significant improvements in energy efficiency. Optimized energy demand management led to a reduction in wasted energy during metro operations, particularly through the utilization of regenerative braking systems. Conclusions: Our findings suggest that integrating AI and IoT technologies into metro systems significantly improves energy efficiency by enabling dynamic energy demand prediction and real-time adjustment of energy consumption. The proposed system is scalable and adaptable, making it suitable for application in metro networks globally, thereby enhancing energy efficiency and supporting sustainable transport initiatives.
Data & Metadataarrow_drop_down
Data & Metadata
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2025-2025
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Evaluating the techno-economic potential of large-scale green hydrogen production via solar, wind, and hybrid energy systems utilizing PEM and alkaline electrolyzers

A short term multistep forecasting model for photovoltaic generation using deep learning model

Latent-dry: Solar drying with latent heat storage in Python, Fortran and TRNSYS

Calculating the impact of replacing legacy batteries with standardized lithium-ion versions in defense aircraft

Three-dimensional computational fluid dynamics (3D-CFD) simulation of hydrogen transport to investigate the effect of output voltage and inlet anode velocity on proton exchange membrane fuel cell performances

Design and experimental characterization of a propane-based reversible dual source/sink heat pump

Further development of offshore floating solar and its design requirements

A review on hybrid energy generation: Cow dung biogas, solar thermal and kinetic energy integration for power production

Assessment and ranking of different vehicles carbon footprint: A comparative study utilizing entropy and TOPSIS methodologies

Predictive Energy Demand and Optimization in Metro Systems Using AI and IoT Technologies

Evaluating the techno-economic potential of large-scale green hydrogen production via solar, wind, and hybrid energy systems utilizing PEM and alkaline electrolyzers

A short term multistep forecasting model for photovoltaic generation using deep learning model

Latent-dry: Solar drying with latent heat storage in Python, Fortran and TRNSYS

Calculating the impact of replacing legacy batteries with standardized lithium-ion versions in defense aircraft

Three-dimensional computational fluid dynamics (3D-CFD) simulation of hydrogen transport to investigate the effect of output voltage and inlet anode velocity on proton exchange membrane fuel cell performances

Design and experimental characterization of a propane-based reversible dual source/sink heat pump

Further development of offshore floating solar and its design requirements

A review on hybrid energy generation: Cow dung biogas, solar thermal and kinetic energy integration for power production

Assessment and ranking of different vehicles carbon footprint: A comparative study utilizing entropy and TOPSIS methodologies

Predictive Energy Demand and Optimization in Metro Systems Using AI and IoT Technologies

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